FPGA-based image processing algorithm design

As one of the most important data sources in machine vision system, camera is facing increasingly strict requirements in video image acquisition, processing and transmission. Through the in-depth analysis of the development trend of the camera, it can be clear that its main pursuit of three goals: improve video image processing performance, reduce costs and enhance flexibility. However, most of the existing video processing platforms have problems such as low data processing efficiency and lack of real-time performance, which is difficult to meet the high performance requirements of modern cameras for video image processing. Because of its high real-time performance, powerful computing power, high integration and flexibility, embedded system has become a promising direction to realize advanced video image processing algorithms. With the embedded platform, the camera system can realize more efficient real-time data processing and higher quality video image output. In the current market, three high-performance embedded processors stand out, namely DSP, ASIC and FPGA. Among them, FPGA chip has become the ideal hardware platform for camera video image processing with its parallel computing capability, rich interface resources and field programmable characteristics. Based on Anlogic EG4S20 FPGA platform, this paper realizes image processing functions, including Bayer format to RGB conversion, gray world algorithm and perfect reflection algorithm. This research makes full use of the powerful computing power of FPGAs to demonstrate image processing and enhancement techniques to address key performance challenges in camera systems.